Partitioned scheduling for sphere decoding with runtime constraints for practical MIMO communication systems

This paper presents an effective scheduling scheme for sphere decoding (SD) with runtime constraints, targeting the practical multiple‐input multiple‐output (MIMO) communication systems where neither the interleaving scheme nor its block size cannot be designed freely. The proposed scheme imposes runtime constraints on SD to distribute the errors due to the early termination of SD. Because the distributed errors may be corrected effectively by forward error correction, the error‐rate performance can be improved; experimental results show that the performance improvement is approximately 2dB in terms of the signal‐to‐noise ratio to achieve a bit‐error rate of 10^?4 in 4 × 4 16‐QAM MIMO systems. Copyright © 2015 John Wiley & Sons, Ltd.     

垂直分层空时码的几种检测算法比较

垂直分层空时码（V-BLAST）是贝尔实验室提出的一种基于多入多出（MIMO）传输方式的空时码系统,其检测算法是MIMO系统的有效检测方法。首先介绍V-BLAST系统的信号模型,在此基础上应用不同的信号估计准则推导出不同的检测算法,最后通过仿真实验对各种算法的性能和优缺点进行了分析和比较。     

Soft‐output MMSE V‐BLAST receiver with MMSE channel estimation under correlated Rician fading MIMO channels

For wireless multiple‐input multiple‐output (MIMO) communications systems, both channel estimation error and spatial channel correlation should be considered when designing an effective signal detection system. In this paper, we propose a new soft‐output MMSE based Vertical Bell Laboratories Layered Space‐Time (V‐BLAST) receiver for spatially‐correlated Rician fading MIMO channels. In this novel receiver, not only the channel estimation errors and channel correlation but also the residual interference cancellation errors are taken into consideration in the computation of the MMSE filter and the log‐likelihood ratio (LLR) of each coded bit. More importantly, our proposed receiver generalizes all existing soft‐output MMSE V‐BLAST receivers, in the sense that, previously proposed soft‐output MMSE V‐BLAST receivers can be derived as the reduced forms of our receiver when the above three considered factors are partially or fully simplified. Simulation results show that the proposed soft‐output MMSE V‐BLAST receiver outperforms the existing receivers with a considerable gain in terms of bit‐error‐rate (BER) performance. Copyright © 2011 John Wiley & Sons, Ltd.     

An enhanced multi-channel bacterial foraging optimization algorithm for MIMO communication system

Channel estimation and optimisation are the main challenging tasks in Multi Input Multi Output (MIMO) wireless communication systems. In this work, a Multi-Channel Bacterial Foraging Optimization Algorithm approach is proposed for the selection of antenna in a transmission area. The main advantage of this method is, it reduces the loss of bandwidth during data transmission effectively. Here, we considered the channel estimation and optimisation for improving the transmission speed and reducing the unused bandwidth. Initially, the message is given to the input of the communication system. Then, the symbol mapping process is performed for converting the message into signals. It will be encoded based on the space–time encoding technique. Here, the single signal is divided into multiple signals and it will be given to the input of space–time precoder. Hence, the multiplexing is applied to transmission channel estimation. In this paper, the Rayleigh channel is selected based on the bandwidth range. This is the Gaussian distribution type channel. Then, the demultiplexing is applied on the obtained signal that is the reverse function of multiplexing, which splits the combined signal arriving from a medium into the original information signal. Furthermore, the long-term evolution technique is used for scheduling the time to channels during transmission. Here, the hidden Markov model technique is employed to predict the status information of the channel. Finally, the signals are decoded and the reconstructed signal is obtained after performing the scheduling process. The experimental results evaluate the performance of the proposed MIMO communication system in terms of bit error rate, mean squared error, average throughput, outage capacity and signal to interference noise ratio.